Response Engineering for Training-Free Alignment of LLMs

A practical tutorial on Best-of-N, self-consistency, Reflexion, and Mixture-of-Agents for improving model responses without retraining.

Authors: Son The Nguyen, Tommy Cheng, Theja Tulabandhula

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Response Engineering · starts at 2:06:50

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This hands-on tutorial explores response engineering techniques that improve language-model outputs at inference time, including Best-of-N selection, self-consistency, Reflexion, and Mixture-of-Agents.

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Son The Nguyen

Author & curator

Son The Nguyen

AI/ML Researcher
PhD Candidate in MIS at UIC

Son The Nguyen is a PhD candidate in Management Information Systems (MIS) at the University of Illinois Chicago, advised by Professor Theja Tulabandhula. His research applies optimization and machine-learning techniques to enhance large language models and agentic AI, with a focus on data quality, alignment, controllability, and reasoning.

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